Classification and Cognition [Hardcover]

Based on Estes' important Fitts Lectures, this volume details a set of psychological concepts and principles that offers a unified interpretation of a wide variety of memory, categorization, and decision-making phenomena. These phenomena are explained via two families of models established by the author: a storage-retrieval model and an adaptive network model. Estes considers whether the models are competing or complementary, offering cogent and instructive arguments for both perspectives. Estes' theory is then applied to two large-scale series of studies on category learning and recognition, providing an integrated understanding of seemingly disparate phenomena. This book is the culmination of the author's more than ten years of research in the field, and stands as a great achievement by one of this century's eminent psychologists. It will be indispensable to a wide variety of behavioral scientists, including mathematical and cognitive psychologists.

1. Introduction and Basic Concepts
1.1. Classification and Cognition: An Overview
1.2. The Array Model Framework
2. Category Structures and Categorization
2.1. Similarity in Theories of Classification
2.2. Predicting Categorization Performance
3. Models for Category Learning
3.1. The Exemplar-Similarity Model
3.2. Network-based Learning Models
4. Categorization and Memory Processing
5. On the Storage and Retrieval of Categorical Information
6. Extensions and Applications of the Exemplar-Similarity Model
7. Categorization and Recognition
8. Categorization and Cognition: Reprise

The research presented here is important for three reasons. First, it sets a standard for rigor, parsimony and theoretical elegance in cognitive modeling. Second. . . it offers a coherent and predictive system for tackling both specific and general issues. Third, it provides formal tools for quantitative modeling of complex systems that researchers in many fields could effectively borrow. -l3&